G-CNN: An Iterative Grid Based Object Detector

@article{Najibi2016GCNNAI,
  title={G-CNN: An Iterative Grid Based Object Detector},
  author={Mahyar Najibi and Mohammad Rastegari and Larry S. Davis},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={2369-2377}
}
We introduce G-CNN, an object detection technique based on CNNs which works without proposal algorithms. G-CNN starts with a multi-scale grid of fixed bounding boxes. We train a regressor to move and scale elements of the grid towards objects iteratively. G-CNN models the problem of object detection as finding a path from a fixed grid to boxes tightly surrounding the objects. G-CNN with around 180 boxes in a multi-scale grid performs comparably to Fast R-CNN which uses around 2K bounding boxes… CONTINUE READING
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